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Expanding the clinical spectrum of 19p13.3 microduplication syndrome: a case report highlighting nephrotic syndrome and literature review.

BMC Pediatr

January 2025

Pediatric Internal Medicine, Yantai Yuhuangding Hospital, No.20 Yuhuangding East Road, Zhifu District, Yantai City, Shandong, 264000, China.

Background: Common clinical findings in patients with 19p13.3 duplication include intrauterine growth restriction, intellectual disability, developmental delay, microcephaly, and distinctive facial features. In this study, we report the case of a patient with 19p13.

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Background: Rare diseases (RDs) are a heterogeneous group of complex and low-prevalence conditions in which the time to establish a definitive diagnosis is often too long. In addition, for most RDs, few to no treatments are available and it is often difficult to find a specialized care team.

Objectives: The project "acERca las enfermedades raras" (in English: "bringing RDs closer") is an initiative primary designed to generate a consensus by a multidisciplinary group of experts to detect the strengths and weaknesses in the public healthcare system concerning the comprehensive care of persons living with a RD (PLWRD) in the region of Catalonia, Spain, where a Network of Clinical Expert Units (Xarxa d'Unitats de Expertesa Clínica or XUEC) was created and is being implemented since 2015.

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Background: Mycoplasma pneumoniae (M pneumoniae, MP) is a common pathogen causing respiratory tract infections, particularly in children. In 2023, a resurgence of MP epidemics was observed in Wuhan, Hubei Province, China. This study aims to examine the epidemiological trends and clinical characteristics of MP infections among children in Wuhan from 2018 to 2024, providing valuable scientific evidence to guide local prevention strategies.

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Introduction: Early antibiotic administration is one of the core treatments of sepsis which associated with reduced mortality rate. However, the appropriate timing of antibiotics remains a controversial issue, especially in patients without septic shock. Here, we reported the outcomes of early antibiotic administration within one hour from the time of infection suspicion in a tertiary care hospital.

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Background: Early detection and diagnosis of cancer are vital to improving outcomes for patients. Artificial intelligence (AI) models have shown promise in the early detection and diagnosis of cancer, but there is limited evidence on methods that fully exploit the longitudinal data stored within electronic health records (EHRs). This review aims to summarise methods currently utilised for prediction of cancer from longitudinal data and provides recommendations on how such models should be developed.

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